Hermes 4 14B on Intel Atom C3538 / C3558 NAS (32 GB)
Can the Intel Atom C3538 / C3558 NAS (32 GB) run Hermes 4 14B?
Barely: it runs very slowly
Very slow. At Q8_0 it needs about 19.7 GB of 26.2 GB usable, with an estimated speed of 0.3 tok/s.
- Best quant
Q8_0- Generation speed
- 0.3 tok/s
- Prompt processing
- 1.2 tok/s
- First token (1K prompt)
- 840.2 s
- Largest safe context
- 40K
Best app to run it on the Intel Atom C3538 / C3558 NAS (32 GB)
On Linux
- Usually the first to support new model architectures.
llama-server -hf bartowski/NousResearch_Hermes-4-14B-GGUF:Q8_0Download Hermes 4 14B
Recommended for the Intel Atom C3538 / C3558 NAS (32 GB): Q8_0. Every other quantization has its own download link in the table below.
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q8_0 file (opens in a new tab)
huggingface.co/bartowski/NousResearch_Hermes-4-14B-GGUF (opens in a new tab)
ollama run hf.co/bartowski/NousResearch_Hermes-4-14B-GGUF:Q8_0Original weights · Hugging Face
Full-precision files from Nous Research, for fine-tuning, vLLM, Transformers.
huggingface.co/NousResearch/Hermes-4-14B (opens in a new tab)
How it’s rated
Match score
To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.
| Model quality | 29.7 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 1.4 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 71.1 / 100 |
Every quantization on the Intel Atom C3538 / C3558 NAS (32 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 9.9 GB | 26.2 GB | 1.1 tok/s | Very slow | 46Fair quality (C) · 46 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 57/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q3_K_M | 11.3 GB | 26.2 GB | 0.9 tok/s | Very slow | 55Good quality (B) · 55 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q4_K_M | 13.1 GB | 26.2 GB | 0.7 tok/s | Very slow | 62Good quality (B) · 62 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 14.5 GB | 26.2 GB | 0.5 tok/s | Very slow | 64Good quality (B) · 64 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 16.2 GB | 26.2 GB | 0.5 tok/s | Very slow | 65Good quality (B) · 65 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 19.7 GB | 26.2 GB | 0.3 tok/s | Very slow | 66Good quality (B) · 66 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 33.6 GB | 26.2 GB | — | Won't run | 66Good quality (B) · 66 of 100: how capable the model is at F16, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
-
66Good quality (B) · 66 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4090
-
66Good quality (B) · 66 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3090
-
65Good quality (B) · 65 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
64Good quality (B) · 64 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
64Good quality (B) · 64 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
64Good quality (B) · 64 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
Quick answers
How much memory does Hermes 4 14B need on the Intel Atom C3538 / C3558 NAS 32GB?
At Q8_0 it needs about 19.7 GB. The Intel Atom C3538 / C3558 NAS 32GB has 26.2 GB usable.
How fast is Hermes 4 14B on the Intel Atom C3538 / C3558 NAS 32GB?
About 0.3 tok/s at Q8_0, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Hermes 4 14B should I use on the Intel Atom C3538 / C3558 NAS 32GB?
Q8_0. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.